Road Damage Detection and Classification Challenge

This challenge is held as one of the 2018 IEEE Big Data Cup

Rules

Basic rule

All algorithms including deep learning can be applied.

Pre-trained models are allowed in the competition.

Participants are restricted to train their algorithms on the road damage dataset train sets.
Collecting additional data for the target attribute labels is not allowed.
If you do so, please mail to the organizers (bdc2018@iis.u-tokyo.ac.jp).
Of course, it is permitted to artificially increase training images using data augmentation,
GANs and so on.

We ask that you respect the spirit of the competition and do not cheat. Hand-labeling is
forbidden.

Please submit source code and trained model in executable form by November 10.
IPython Notebook is desirable for the source code submission, but any programing languages are acceptable.
The organizers will verify the reproducibility of the algorithm and determine the final winner.

Even If you are submitting a paper with similar contents to other workshops, when you add 30% extension, you can submit.

The technical paper does not affect the ranking decision.

If you describe contents that will contribute to the future of road damage detection, such as suggestions for improvement on our dataset,
in the technical paper, we will present special prize (special products of Japan)